Hadoop Appliances and Teradata

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The first part discusses the use of Hadoop appliances. On the other side of the equation are unquantifiable but nevertheless important considerations. These include the risks involved with implementing Hadoop on your own: what are the dangers involved with unforeseen delays to your implementation? Even if there are no delays it will always take longer compared to having an appliance that is pre-configured and ready to run, and what are the opportunity costs associated with that and how will that affect productivity? There are similar questions with respect to high availability and performance. We cannot answer these questions specifically (though we will quote some research into these areas) because every business is different and uses of Hadoop vary widely. However, the answers to these questions need to be balanced against any total cost of ownership considerations.

Alternatively, consider why you
are implementing Hadoop in the first place. Do you want to spend a lot of time setting up and running a fancy new technical infrastructure or do you think your Hadoop environment will help
to provide you with insights into your company and its customers that will
help you to run your organisation more efficiently and with greater profit? We think the answer is probably the latter. In that case, why not let someone else make the hard yards and leave you to score the touchdown?

It is the view of Bloor Research that, when all relevant factors are taken into account, an appliance based approach will provide faster time to value, a more rapid return on your investment and, more often than not, a lower total cost of ownership as you measure it over the years – not just the first year itself. It will allow you to focus on what you really want: better and more timely analytics.

fact, many of the arguments put forward here apply to all sorts of appliances
but we will be focused specifically on Hadoop appliances. In this context there are arguments both for and against the implementation of Hadoop appliances and while we believe that
the former outweigh the latter we must acknowledge that some of the arguments against the use of Hadoop appliances

are both cogent and valid. In the second part of this paper we will discuss specific features of the Teradata Appliance for Hadoop and how this particular appliance not only offers the advantages of appliances in general but also overcomes some of the objections commonly raised against appliance-based deployments.

In our view, the first of these is all too often a mirage. It is too easy to consider capital expenditure in isolation without respect to operating costs; and operating costs do not just mean maintenance, they include the time and effort involved in implementing the solution, administering and managing performance on an ongoing basis, and ensuring high availability. All of these factors add up to total cost of ownership.

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